Many entities may wish to improve performance by reducing and/or eliminating accidents, abuse, operating, maintenance, and/or replacement expenses, and/or other costs associated with operating one or more vehicles. The economic, environmental, and social value of such benefits is significant, especially for commercial fleets and overall driving safety.
There exists a large and growing market for vehicle monitoring systems and methods that facilitate the collection of information related to the contributing causes of vehicle incidents, such as accidents, and provide objective driver evaluation to determine the quality of driving practices. There is also a market for systems and methods for recording various operating parameters over time so as to provide a historical driver profile record to uncover deviations from suggested driving practices, which may further improve driving behavior.
Recent advances for such systems and methods include relying on global navigation satellite systems (GNSS) to track vehicle operation, as well as additional sensors such as gyroscopes, accelerometers, wheel speed pulse, etc. which allow various driving behaviors such as speeding and sudden acceleration to be determined. However, existing solutions don't analyze driver behavior in the context of a map, which provides a model of real world paths (e.g., roads). Furthermore, existing solutions are limited to discrete analysis and do not allow continuous evaluation of driver performance.
Thus there is a need for a driver behavior engine that accurately monitors various parameters to allow analysis of driving behaviors, and that provides contiguous evaluation elements for such driving behaviors.